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   "source": [
    "### <center>San Jose State University<br>Department of Applied Data Science<br><br>**DATA 200<br>Computational Programming for Data Analytics**<br><br>Spring 2024<br>Instructor: Ron Mak</center>"
   ]
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   "source": [
    "## 9.12.1 Python Standard Library Module `csv` "
   ]
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   "source": [
    "#### The CSV (comma-separated values) format is very common for datasets you may find on the web. \n",
    "#### An example CSV file:\n",
    "```\n",
    "Make,Model,Year,Price\n",
    "Honda,Accord,2005,1500\n",
    "Toyata,Prius,2010,9000\n",
    "Volvo,240 DL,1995,500\n",
    "Chevy,Nova,1975,200\n",
    "Ford,,2000,400\n",
    "```\n",
    "#### There is one line per record, and values are separated by commas. Often, the first line contains the column headers."
   ]
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   "metadata": {},
   "source": [
    "### Writing to a CSV File"
   ]
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Python's `csv` module supports reading and writing CSV files."
   ]
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   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "import csv"
   ]
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   "source": [
    "with open('UsedCars.csv', mode='w', newline='') as cars:\n",
    "    writer = csv.writer(cars)\n",
    "    writer.writerow(['Make', 'Model', 'Year', 'Price'])\n",
    "    writer.writerow(['Honda', 'Accord', 2005, 1500])\n",
    "    writer.writerow(['Toyata', 'Prius', 2010, 9000])\n",
    "    writer.writerow(['Volvo', '240 DL', 1995, 500])\n",
    "    writer.writerow(['Chevy', 'Nova', 1975, 200])\n",
    "    writer.writerow(['Ford', '', 2000, 400])"
   ]
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reading from a CSV File"
   ]
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('UsedCars.csv', 'r', newline='') as cars:\n",
    "    reader = csv.reader(cars)\n",
    "    first = True\n",
    "\n",
    "    for record in reader:  \n",
    "        if first:\n",
    "            for header in record:\n",
    "                print(f'{header:<10}', end='')\n",
    "            print()\n",
    "            first = False\n",
    "        else:\n",
    "            make, model, year, price = record\n",
    "            print(f'{make:<10}{model:<10}{year:<10}{price:<10}')"
   ]
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Commas and Quotes in CSV Data Fields"
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### If there are consecutive commas in a CSV record with no value between them, then that is an empty field, as in the Ford line in the example:\n",
    "```\n",
    "Ford,,2000,400\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Non-numeric values in a CSV files can each be surrounded by double quotes. While writing a CSV file, if a value contains a comma, then enclose the value in quotes. That value will be written with double quotes in the file.\n",
    "#### The `csv.writer()` function has parameters that control what character separates values (the delimiter, default is a comma), what the quote character is, and what values to enclose in quotes."
   ]
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('UsedCars.csv', mode='w', newline='') as cars:\n",
    "    writer = csv.writer(cars, delimiter='/', quotechar='\"', \n",
    "                        quoting=csv.QUOTE_NONNUMERIC)\n",
    "    writer.writerow(['Make', 'Model', 'Year', 'Price'])\n",
    "    writer.writerow(['Honda', 'Accord', 2005, 1500])\n",
    "    writer.writerow(['Toyata', 'Prius', 2010, 9000])\n",
    "    writer.writerow(['Volvo', '240 DL', 1995, 500])\n",
    "    writer.writerow(['Chevy', 'Nova', 1975, 200])\n",
    "    writer.writerow(['Ford', '', 2000, 400])"
   ]
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   "execution_count": null,
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   "source": [
    "##########################################################################\n",
    "# (C) Copyright 2019 by Deitel & Associates, Inc. and                    #\n",
    "# Pearson Education, Inc. All Rights Reserved.                           #\n",
    "#                                                                        #\n",
    "# DISCLAIMER: The authors and publisher of this book have used their     #\n",
    "# best efforts in preparing the book. These efforts include the          #\n",
    "# development, research, and testing of the theories and programs        #\n",
    "# to determine their effectiveness. The authors and publisher make       #\n",
    "# no warranty of any kind, expressed or implied, with regard to these    #\n",
    "# programs or to the documentation contained in these books. The authors #\n",
    "# and publisher shall not be liable in any event for incidental or       #\n",
    "# consequential damages in connection with, or arising out of, the       #\n",
    "# furnishing, performance, or use of these programs.                     #\n",
    "##########################################################################\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Additional material (C) Copyright 2023 by Ronald Mak"
   ]
  }
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